Michael Emmerich
Universitair hoofddocent
- Naam
- Dr. M.T.M. Emmerich
- Telefoon
- +31 71 527 7094
- m.t.m.emmerich@liacs.leidenuniv.nl
Meer informatie over Michael Emmerich
Nieuws
-
LIACS onderdeel van Horizon 2020 project over social media analytics -
Informatici uit Leiden en Eindhoven optimaliseren gebouwontwerpen -
Studium Generale-reeks over complexe netwerken afgetrapt -
Multiple-criteria landscapes with valleys and hills -
Algorithms help improve building design -
13th LCDS meeting: combining data science and drug discovery
Foundations of multicriteria optimization and complex systems research:
- Set oriented optimization by numerical and natural computing methods
- Theory of indicators and preference models in multicriteria optimization
- Complex networks and parameterized computational complexity Applications of these algorithms in:
- Drug Discovery and Chemoinformatics
- Sustainable Engineering Design
- Scientific Data Management and Databases
I am involved in the Data Driven Drug Discovery Network (D4N) and in the Leiden Complex Network Network (LCN2).
For more information, see my personal website.
Universitair hoofddocent
- Wiskunde en Natuurwetenschappen
- Leiden Inst. Advanced Computer Sciences
- Stein B. van, Wang H., Kowalczyk W., Emmerich M.T.M. & Bäck T.H.W. (2019), Cluster-based Kriging approximation algorithms for complexity reduction, Applied Intelligence : 1-14.
- Yevseyeva I., Lenselink E.B., Vries A. de, IJzerman A.P., Deutz A.H. & Emmerich M.T.M. (2019), Application of portfolio optimization to drug discovery, Information Sciences 475: 29-43.
- Blom K. van der, Yang K., Bäck T. & Emmerich M.T.M. (2019), Towards Multi-objective Mixed Integer Evolution Strategies. In: Emmerich M.T.M., Deutz A.H., Hille S.C., Sergeyev Y.D. (red.) Proceedings LeGO - 14th International Global Optimization Workshop. nr. 2070: AIP Publishing. 020046.
- Yang K., Blom K. van der, Bäck T. & Emmerich M.T.M. (2019), Towards Single- and Multiobjective Bayesian Global Optimization for Mixed Integer Problems. In: Emmerich M.T.M., Deutz A.H., Hille S.C., Sergeyev Y.D. (red.) Proceedings LeGO - 14th International Global Optimization Workshop: AIP Publishing. nr. 2070: AIP Publishing. 020044.
- Blom K. van der, Boonstra S., Hofmeyer H. & Emmerich M.T.M. (2019), Analysing Optimisation Data for Multicriteria Building Spatial Design. In: Deb K., Goodman E., Coello Coello C.A., Klamroth K., Miettinen K., Mostaghim S., Reed P. (red.) Evolutionary Multi-Criterion Optimization. nr. 11411 Cham: Springer. 671-682.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2019), Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies, Evolutionary Computation .
- Wang H., Bäck T.H.W., Plaat A., Emmerich, M.T.M. & Preuss M. (2019), On the potential of evolution strategies for neural network weight optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion.: ACM. 191-192.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2019), Towards Self-Adaptive Efficient Global Optimization. In: AIP Conference Proceedings. nr. 2070: AIP Publishing. 020056.
- Boonstra S., Blom K. van der, Hofmeyer H., Buijs J. van den & Emmerich M.T.M. (2018), Coupling Between a Building Spatial Design Optimisation Toolbox and BouwConnect BIM. In: Mutis I., Hartmann T. (red.) Advances in Informatics and Computing in Civil and Construction Engineering - Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management. Cham: Springer. 95-102.
- Kerschke P., Wang H., Preuss M., Grimme G., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2018), Search Dynamics on Multimodal Multi-Objective Problems, Evolutionary Computation Journal : 1-33.
- Li L., Chen H., Li J., Jing N. & Emmerich M.T.M. (2018), Preference-Based Evolutionary Many-Objective Optimization for Agile Satellite Mission Planning, IEEE Access 6: 40963-40978.
- Blom K. van der, Boonstra S., Wang H., Hofmeyer H. & Emmerich M.T.M. (2018), Evaluating Memetic Building Spatial Design Optimisation Using Hypervolume Indicator Gradient Ascent. In: Trujillo L., Schütze O., Maldonado Y., Valle P. (red.) Numerical and Evolutionary Optimization – NEO 2017. Studies in Computational Intelligence nr. 785 Cham: Springer. 62-86.
- Boonstra S., Blom K.. van der, Hofmeyer H., Emmerich M.T.M., Schijndel J. van & Wilde P. de (2018), Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation, Advanced Engineering Informatics 36: 86-100.
- Zhao J., Jiao L., Liu F., Fernandes V.B., Yevseyeva I., Xia S. & Emmerich M.T.M. (2018), 3D fast convex-hull-based evolutionary multiobjective optimization algorithm, Applied Soft Computing 67: 322-336.
- Emmerich M.T.M., Shir M.O. & Wang H. (2018), Evolution Strategies. In: Martí R., Panos P., Resende G.C.M. (red.) Handbook of Heuristics. Cham: Springer International Publishing. 1-31.
- Yevseyeva I., Lenselink E.B., Vries A. de, IJzerman A.P., Deutz A.H. & Emmerich M.T.M. (2018), Application of portfolio optimization to drug discovery, Information Sciences 475: 29-43.
- Wang H., Emmerich M.T.M. & Plaat A. (2018), Assessing the Potential of Classical Q-learning in General Game Playing.
- Emmerich M.T.M. & Deutz A.H. (2018), A tutorial on multiobjective optimization: fundamentals and evolutionary methods, Natural computing 17(3): 585-609.
- Asep Maulana A., Deutz A.H., Schultes E. & Emmerich M.T.M. (2018), Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. In: Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Advances in Intelligent Systems and Computing, volume 674 Cham: Springer. 163-176.
- Lytvyn V., Dosyn D., Emmerich M.T.M. & Yevseyeva I. (2018), Content Formation Method in the Web Systems. In: Lytvyn V., Sharonova N., Hamon T., Vysotska V., Grabar N., Kowalska-Styczen A., Jonek-Kowalska I. (red.) Proceedings of the 2nd International Conference on Computational Linguistics and Intelligent Systems. Volume I: Main Conference. nr. 2136. 42-61.
- Wang H., Emmerich M.T.M. & Bäck T.H.W. (2018), Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization. In: 2018 IEEE Congress on Evolutionary Computation (CEC 2018).: IEEE. 1-8.
- Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (red.) (2018), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI Advances in Intelligent Systems and Computing nr. 674. Cham: Springer.
- Li L., Chen H., Li J., Jing N. & Emmerich M.T.M. (2018), Integrating region preferences in multiobjective evolutionary algorithms based on decomposition. In: 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI).: IEEE. 379-384.
- Bringmann K., Cabello S. & Emmerich M.T.M. (2018), Maximum Volume Subset Selection for Anchored Boxes. In: Aronov B., Katz M.J. (red.) Leibniz International Proceedings in Informatics. nr. 77 Germany: Dagstuhl Publishing. 22.1-22.15.
- Wang H., Emmerich M.T.M. & Plaat A. (2018), Monte Carlo Q-learning for General Game Playing.
- Palar P.S., Yang K., Shimoyama K., Emmerich M.T.M. & Bäck T.H.W. (2018), Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement. In: GECCO'18 Proceedings of the Genetic and Evolutionary Computation Conference Companion.: ACM. 1333-1340.
- Yang K., Emmerich M.T.M., Deutz A.H. & Bäck T.H.W. (2018), Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient, Swarm and Evolutionary Computation 44: 945-956.
- Li L., Wang Y., Trautmann H., Jing N. & Emmerich M.T.M. (2018), Multiobjective evolutionary algorithms based on target region preferences, Swarm and Evolutionary Computation 40: 196-215.
- Zhao J., Jiao L., Xia S., Fernandes V.B., Yevseyeva I., Zhou Y. & Emmerich M.T.M. (2018), Multiobjective Sparse Ensemble Learning by Means of Evolutionary Algorithms, Decision Support Systems 111: 86-100.
- Wang H., Bäck T.H.W. & Emmerich M.T.M. (2018), Multi-point Efficient Global Optimization Using Niching Evolution Strategy. In: Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Advances in Intelligent Systems and Computing, volume 674 Cham: Springer. 146-162.
- Verhoef W., Deutz A.H. & Emmerich M.T.M. (2018), On Gradient-Based and Swarm-Based Algorithms for Set-Oriented Bicriteria Optimization. In: Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Advances in Intelligent Systems and Computing, volume 674 Cham: Springer. 18-36.
- Nezhinsky A. & Emmerich M.T.M. (2018), Parameter identification of stochastic gene regulation models by indicator-based evolutionary level set approximation. In: Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Advances in Intelligent Systems and Computing, volume 674 Cham: Springer. 50-64.
- Li L., Chen H., Wu J., Li J., Jing N. & Emmerich M.T.M. (2018), Preference-based evolutionary algorithms for many-objective mission planning of agile earth observation satellites. In: Aguirre H. (red.) Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: ACM. 187-188.
- Basto-Fernandes V., Yevseyeva I., Ruano-Ordás D., Zhao J., Fdez-Riverola F., Méndez J.R. & Emmerich M.T.M. (2018), Quadcriteria Optimization of Binary Classifiers: Error Rates, Coverage, and Complexity. In: Tantar A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Advances in Intelligent Systems and Computing, volume 674 Cham: Springer. 37-49.
- Hernández V.A., Schütze O., Wang H., Deutz A.H. & Emmerich M.T.M. (2018), The Set-Based Hypervolume Newton Method for Bi-Objective Optimization, IEEE Transactions on Cybernetics .
- Pappa G.L., Emmerich M.T.M., Bazzan A., Browne W., Deb K., Doerr C., Ðurasević M., Epitropakis M.G., Haraldsson S.O., Jakobovic D., Kerschke P., Krawiec K., Lehre P.K., Li X., Lissovoi A., Malo P., Martí L., Mei Y., Merelo J.J., Miller J.F., Moraglio A., Nebro A.J., Nguyen S., Ochoa G., Oliveto P., Picek S., Pillay N., Preuss M., Schoenauer M., Senkerik R., Sinha A., Shir O., Sudholt D., Whitley D., Wineberg M., Woodward J. & Zhang M. (2018), Tutorials at PPSN 2018. In: Auger A., Fonseca C.M., Lourenço N., Machado P., Paquete L., Whitley D. (red.) International Conference on Parallel Problem Solving from Nature. nr. Lecture Notes in Computer Science, volume 11102 Cham: Springer. 477-489.
- Baghoussi Y., Mendes-Moreira J. & Emmerich M.T.M. (2018), Updating a robust optimization model for improving bus schedules. In: 2018 10th International Conference on Communication Systems & Networks (COMSNETS).: IEEE. 619-624.
- Vysotska V., Fernandes V.B. & Emmerich M.T.M. (2018), Web Content Support Method in Electronic Business Systems. In: Lytvyn V., Sharonova N., Hamon T., Vysotska V., Grabar N., Kowalska-Styczen A., Jonek-Kowalska I. (red.) Proceedings of the 2nd International Conference on Computational Linguistics and Intelligent Systems. Volume I: Main Conference. nr. 2136. 20-41.
- Zhao J., Basto-Fernandes V., Jiao L., Yevseyeva I., Asep Maulana A., Li R., Bäck T.H.W., Tang K. & Emmerich M.T.M. (2017), Corrigendum to ‘Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms’ [Information Sciences volumes 367–368 (2016) 80–104], Information Sciences 403-404: 55-55.
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), Time complexity reduction in efficient global optimization using cluster kriging. In: GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. New York: ACM. 889-896.
- Boonstra S., Blom K. van der, Hofmeyer H. & Michael T. M.Emmerich (2017), Combined Super-Structured and Super-Structure Free Optimisation of Building Spatial Designs. In: Koch C., Tizani W., Ninic J. (red.) Intelligent computing in engineering.. 23-34.
- Basto-Fernandez V., Yevseyeva I., Mendez J.R., Zhao J., Fdez-Riverola F. & Emmerich M.T.M. (2017), Corrigendum to “A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification” [Applied Soft Computing Volume 48 (2016) 111–123], Applied Soft Computing 55: 565-565.
- Liu L.-Y., Basto-Fernandes V.,Yevseyeva I., Kok J.N. & Emmerich M.T.M. (2017), Indicator-Based Evolutionary Level Set Approximation: Mixed Mutation Strategy and Extended Analysis. In: Vicente J.M.F., Álvarez-Sánchez J.R., de la Paz F., López J.T.M., Hojjat A. (red.) Natural and Artificial Computation for Biomedicine and Neuroscience. nr. LNCS, volume 10337 Cham: Springer. 146-159.
- Blom K. van der, Boonstra S., Hofmeyer H., Bäck T. & Michael T. M.Emmerich (2017), Configuring Advanced Evolutionary Algorithms for Multicriteria Building Spatial Design Optimisation: IEEE. 1803-1810.
- Janus T., Foussette C., Urselmann M., Tlatlik S., Gottschalk A., Emmerich M.T.M., Bäck T.H.W. & Engell S. (2017), Optimization-Based Process Synthesis Based on a Commercial Flowsheet Simulator, CHEMIE INGENIEUR TECHNIK 89(5): 655-664.
- Li L., Yao F., Jing N. & Emmerich M.T.M. (2017), Preference incorporation to solve multi-objective mission planning of agile earth observation satellites. In: 2017 IEEE Congress on Evolutionary Computation (CEC). Piscataway, NY: IEEE Xplore. 1366-1373.
- Allmendinger R., Emmerich M.T.M., Hakanen J., Jin Y. & Rigoni E. (2017), Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case, JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 24(1-2): 5-24.
- Li L., Yevseyeva I., Basto-Fernandes V., Trautmann H., Jing N. & Emmerich M.T.M. (2017), Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In: Trautmann H. (red.) Evolutionary Multi-Criteron Optomization. EMO 2017. nr. Lecture Notes in Computer Science LNCS 10173 Cham: Springer. 406-421.
- Yang K., Emmerich M.T.M., Deutz A.H. & Fonseca C.M. (2017), Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time. In: Trautmann H., Rudolph G., Klamroth K., Schütze O., Wiecek M., Jin Y., Grimme C. (red.) International Conference on Evolutionary Multi-Criterion Optimization. nr. LNCS Volume 10173 Cham: Springer. 685-700.
- Kerschke P., Wang H., Preuss M., Grimme C., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2017), Towards analyzing multimodality of multiobjective landscapes: PPSN 2016 best paper award. [overig]
- Wang H., Stein B. van, Emmerich M.T.M. & Bäck T.H.W. (2017), A New Acquisition Function for Bayesian optimization based on the moment-generating function. In: Hao Wang, Stein B. van,Michael T. M.Emmerich, Bäck T.H.W. (red.) 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Banff, AB, Canada: IEEE. 507-512.
- Wang Y., Li L., Yang K. & Emmerich M.T.M. (2017), A new approach to target region based multiobjective evolutionary algorithms. In: 2017 IEEE Congress on Evolutionary Computation (CEC). Piscataway, NY: IEEE press. 1757-1764.
- Basto-Fernandes V., Yevseyeva I., Deutz A. & Emmerich M.T.M. (2017), A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms. In: Emmerich M.T.M., Deutz A., Schütze O., Legrand P., Tantar E., Tantar A.A. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII. Studies in Computational Intelligence nr. 662 Cham: Springer. 3-23.
- Asep Maulana A., Deutz A.H. & Emmerich M.T.M. (2017), Community Detection in NK Landscapes - An Empirical Study of Complexity Transitions in Interactive Networks. In: Tantar A.A.., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. nr. Volume 674 Cham: Springer. 163-176.
- Emmerich M.T.M., Deutz A.H., Schütze O., Legrand P., Tantar E. & Tantar A.-A. (2017), EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII Studies in Computational Intelligence nr. SCI, volume 662. Heidelberg: Springer.
- Wang H., Deutz A.H., Bäck T.H.W. & Emmerich M.T.M. (2017), Hypervolume Indicator Gradient Ascent Multi-objective Optimization. In: Trautmann H., Rudolph G., Klamroth K., Schütze O., Wiecek M., Jin Y., Grimme C. (red.) Evolutionary Multi-Criterion Optimization. nr. 10173 Cham: Springer International Publishing. 654-669.
- Maulana A., Kefalas M. & Emmerich M.T.M. (2017), Immunization of networks using genetic algorithms and multiobjective metaheuristics. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI 2017).: IEEE. 1-8.
- Bringmann K., Cabello S. & Emmerich M.T.M. (2017), Maximum Volume Subset Selection for Anchored Boxes. In: Boris A., Katz M.J. (red.) 33rd International Symposium on Computational Geometry (SoCG 2017). Dagstuhl, Germany: Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik. 22.1-22.15.
- Asep Maulana A., Gametto V., Garlaschelli D., Yevesyeva I. & Michael T. M.Emmerich (2017), Modularities Maximization in Multiplex network Analysis Using Many-Objective Optimization nr. 2016 IEEE Symposium Series on Computational Intelligence (SSCI): IEEE. 1-8.
- Janus T., Foussette C., Urselmann M., Tlatlik S., Gottschalk A., Emmerich M.T.M., Bäck T.H.W. & Engell S. (2017), Optimierungsbasierte Prozesssynthese auf Basis eines kommerziellen Flowsheet Simulators, CHEMIE INGENIEUR TECHNIK 89(5): 655-664.
- Bagheri S., Konen W., Emmerich M.T.M. & Bäck T.H.W. (2017), Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets, Applied Soft Computing 61: 377-393.
- Emmerich M.T.M., Yang K., Deutz A.H., Wang H. & Fonseca C.M. (2016), A Multicriteria Generalization of Bayesian Global Optimization. In: Pardalos M.P., Zhigljavsky A., Zilinskas J. (red.) Advances in Stochastic and Deterministic Global Optimization. Optimization and its Applications nr. 107: Springer. 229-243.
- Stein B. van, Hao Wang, Kowalczyk W.J., Michael T. M.Emmerich & Bäck T.H.W. (2016), Fuzzy clustering for Optimally Weighted Cluster Kriging. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).: IEEE. 978-1-5090-0627-4.
- Zhao J., Basto Fernandes V., Jiao L., Yevseyeva I., Asep Maulana A., Li R., Bäck T.H.W., Tang T. & Michael T. M.Emmerich (2016), Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms, Information Sciences 367-368: 80–104.
- Michael T. M.Emmerich, Deutz A.H., Li L., Asep Maulana A. & Yevseyeva I. (2016), Maximizing Consensus in Portfolio Selection in Multicriteria Group Decision Making, Procedia Computer Science 100: 848–855.
- Yevseyeva I., Basto Fernandes V., Moorsel A. van, Janicke H. & Michael T. M.Emmerich (2016), Two-stage Security Controls Selection, Procedia Computer Science 100: 971-978.
- Hao Wang, Ren Y., Deutz A. & Michael T. M.Emmerich (2016), On Steering Dominated Points in Hypervolume Indicator Gradient Ascent for Bi-Objective Optimization. In: Schuetze O., Trujillo L., Legrand P., Maldonado Y. (red.) NEO 2015: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico. Studies in Computational Intelligence nr. Studies in Computational Intelligence 663: Springer International Publishing. 175-203.
- Basto-Fernandes V., Yevseyeva I., Méndez J.R., Zhao J., Fdez-Riverola F. & Emmerich M.T.M (2016), A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification, Applied Soft Computing 48: 111-123.
- Yang Z., Michael T. M.Emmerich, Bäck T.H.W. & Kok J.N. (2016), Multi-objective inventory routing with uncertain demand using population-based metaheuristics, Integrated Computer-Aided Engineering 23(3): 205-220.
- Yang Z., Osta J.P. van, Veen B. van, Krevelen R. van, Stam A., Kok J.N., Bäck T.H.W. & Emmerich M.T.M. (2017), Dynamic vehicle routing with time windows in theory and practice, Natural computing 16(1): 119–134.
- Blom K. van der, Boonstra S., Hofmeyer H. & Michael T. M.Emmerich (2016), A super-structure based optimisation approach for building spatial designs. In: Papadrakakis M., Papadopoulos V., Stefanou G., Plevris V. (red.) Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering.: National Technical University of Athens. 3409-3422.
- Hao Wang, Michael T. M.Emmerich & Bäck T. (2016), Balancing Risk and Expected Gain in Kriging-based Global Optimization. In: 2016 IEEE Congress on Evolutionary Computation (CEC).: IEEE Publishing. 719-727.
- Asep Maulana A., Gemmetto V., Garlaschelli D. & Emmerich M.T.M. (2016), Computing Pareto Fronts of Modularities in Multiplex Economic Network Analysis. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI).: IEEE Xplore. 1-8.
- Stein B. van, Wang H., Kowalczyk W., Michael T. M.Emmerich & Bäck T. (2016), Fuzzy clustering for Optimally Weighted Cluster Kriging. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).: IEEE. 939-945.
- Cai F., Hao Wang, Tang X., Michael T. M.Emmerich & Verbeek F.J. (2016), Fuzzy Criteria in Multi-objective Feature Selection for Unsupervised Learning, Procedia Computer Science 102: 51-58.
- Blom K. van der, Boonstra S., Hofmeyer H. & Michael T. M.Emmerich (2016), Multicriteria building spatial design with mixed integer evolutionary algorithms. In: Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G., Paechter B. (red.) Parallel Problem Solving from Nature – PPSN XIV. nr. LNCS 9921: Springer International Publishing AG. 453-462.
- Blom K. van der, Boonstra S., Hofmeyer H. & Michael T. M.Emmerich (2016), Multicriteria Building Spatial Design with Mixed Integer Evolutionary Algorithms. In: Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G., Paechter B. (red.) Parallel Problem Solving from Nature – PPSN XIV 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings. nr. 9921 Cham: Springer International Publishers. 453-462.
- Yang K., Li L., Deutz A.H., Bäck T.H.W. & Michael T. M.Emmerich (2016), Preference-based multiobjective optimization using truncated expected hypervolume improvement. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),.: IEEE Publishing.
- Yang K., Li L., Deutz A.H., Bäck Th. & Michael T. M.Emmerich (2016), Preference-based multiobjective optimization using truncated expected hypervolume improvement. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).: IEEE. 276-281.
- Urselmann M., Foussette C., Janus T., Tlatlik S., Gottschalk A., Emmerich, M.T.M., Engell S. & Bäck T. (2016), Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis. In: Friedrich T. (red.) Proceedings of the Genetic and Evolutionary Computation Conference 2016. New York: ACM. 1029-1036.
- Yang Z., Hao Wang, Yang K., Bäck T. & Michael T. M.Emmerich (2016), SMS-EMOA with multiple dynamic reference points. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD),.: IEEE Publishing. 282-288.
- Yang Z., Li L., Deutz A.H., Bäck T. & Michael T. M.Emmerich (2016), SMS-EMOA with multiple dynamic reference points. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).: IEEE. 282-288.
- Boonstra S., Blom K. van der, Hofmeyer H., Amor R. & Emmerich M.T.M. (2016), Super-structure and super-structure free design search space representations for a building spatial design in multi-disciplinary building optimisation. In: Electronic proceedings of the 23rd International Workshop of the European Group for Intelligent Computing in Engineering.: Jagiellonian University ZPGK. 1-10.
- Kerschke P., Hao Wang, Preuss M., Grimme C., Deutz A., Trautmann H. & Michael T. M.Emmerich (2016), Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. In: Handl J., Hart E., Lewis P. R. , López-Ibáñez M., Ochoa G., Paechter B. (red.) Parallel Problem Solving from Nature – PPSN XIV.: Springer International Publishing. 962-972.
- Kerschke P., Wang H., Preuss M., Grimme C., Deutz A.H., Trautmann H. & Michael T. M.Emmerich (2016), Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. In: Handl J., Hart E., Lewis P.R., López-Ibáñez M., Ochoa G., Paechter B. (red.) Parallel Problem Solving from Nature – PPSN XIV 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings. nr. 9921 Cham: Springer International Publishers. 962-972.
- Yang K., Deutz A.H., Yang Z., Bäck T.H.W. & Michael T. M.Emmerich (2016), Truncated expected hypervolume improvement: Exact computation and application. In: 2016 IEEE Congress on Evolutionary Computation (CEC).: IEEE Publishing. 4350-4357.
- Yang K., Deutz A.H., Yang Z., Bäck T. & Michael T. M.Emmerich (2016), Truncated expected hypervolume improvement:Exact computation and application. In: 2016 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 4350-4357.
- Stein B. van, Wang H., Kowalczyk W., Bäck T. & Emmerich M. (2015), Optimally Weighted Cluster Kriging for Big Data Regression. In: Fromont E., Bie T. de, Leeuwen M. van (red.) Advances in Intelligent Data Analysis XIV. nr. LNCS 9385 Cham: Springer International Publishing. 310-321.
- Rosa Sequeira F., Frantz R.Z., Yevseyeva I., Michael T. M.Emmerich & Basto-Fernandes V. (2015), An EAI Based Integration Solution for Science and Research Outcomes Information Management, Procedia Computer Science 64: 894-901.
- Urselmann M., Engell S., Foussette C., Bäck T., Janus T., Tlatlik S., Gottschalk A & Emmerich M (2015), Designoptimierung thermischer Trennverfahren mit memetischen Algorithmen und Aspen Plus Prozessmodellen, Chemie Ingenieur Technik 87(8): 1060.
- Koch, P., Wagner, T., Emmerich M. T. M., Bäck, T., Konen & W (2015), Efficient multi-criteria optimization on noisy machine learning problems, Applied Soft Computing 29: 357-370.
- Michael T. M.Emmerich, Deutz A.H. & Yevseyeva I. (2015), A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making, Procedia Computer Science 64(2015): 993-1000.
- Yang Z., Emmerich M.T.M., Bäck & .H.W. (2015), Ant based solver for dynamic vehicle routing problem with time windows and multiple priorities. In: Obayashi S., Poloni C., Murata T. (red.) Proceedings CEC 2015.: IEEE Xplore. 2813-2819.
- Wang H., Schwab I. & Emmerich M.T.M. (2015), Comparing Knowledge Representation Forms in Empirical Model Building. In: Schwab I., Moergestel L. van, Goncalves G. (red.) Proceedings of the Fourth International Conference on Intelligent Systems and Application. Intelli 2015. Wilmington, DE, U.S.A.: IARIA. 170-178.
- Wang P., Emmerich M.T.M., Li R., Tang K., Bäck T.H.W. & Yao X. (2015), Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance, IEEE Transactions on Evolutionary Computation 19(2): 188-200.
- Urselmann M., Foussette C., Janus T., Tlatlik S., Gottschalk A., Emmerich M.T.M. & Bäck T.H.W. (2015), "Derivative-Free Design Optimization of Chemical Processes by a Memetic Algorithm". In: Proceedings UK Workshop on Computational Intelligence..
- Tantar A.A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L. & Luchian H. (red.) (2015), EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VI Advances in Intelligent Systems and Computing. Switzerland: Springer Nature.
- Yang K., Gaida D., Bäck T. & Emmerich M. (2015), Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant. Sendai, Japan: IEEE. 1934-1942.
- Yang K., Gaida D., Bäck T.H.W. & Emmerich M.T.M. (2015), Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant. In: Obayashi S., Poloni C., Murata T. (red.) 2015 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 1934-1942.
- Hupkens I., Deutz A.H., Yang K & Emmerich M.T.M. (2015), Faster Exact Algorithms for Computing Expected Hypervolume Improvement. In: Gaspar-Cunha A., Henggeler Antunes C., Coello Coello C.A. (red.) Evolutionary Multi-Criterion Optimization. nr. 9019: Springer International Publishing. 65-79.
- Hupkens I., Deutz A., Yang K. & Emmerich M. (2015), Faster Exact Algorithms for Computing Expected Hypervolume Improvement. In: Gaspar-Cunha A., Henggeler Antunes C., Coello C. (red.) Lecture Notes in Computer Science. nr. 9019 2015 Guimaraes: Springer Link. 65-79.
- Yang Z., Emmerich M., Bäck T. & Kok J. (2015), Multicriteria Inventory Routing by Cooperative Swarms and Evolutionary Algorithms. In: Ferrández Vicente J.M., Álvarez-Sánchez J.R., Paz López F. de la, Toledo-Moreo F.C.O.J., Adeli H. (red.) Bioinspired Computation in Artificial Systems. nr. 9108 2015. 127-137.
- Yang Z., Emmerich M.T.M., Bäck T.H.W. & Kok J.N. (2015), Multicriteria Inventory Routing by Cooperative Swarms and Evolutionary Algorithms. In: Ferrandez Vicente J., Alvarez-Sanchez J., Paz Lopez F. de la, Toledo-Moreo F., Adeli H. (red.) Bioinspired Computation in Artificial Systems. IWINAC 2015.. nr. LNCS 9108 Cham: Springer. 127-137.
- Hao Wang, Bäck T.H.W. & Emmerich M.T.M. (2015), Multi-point efficient global optimization using Niching Evolution Strategy. In: Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI.: Springer.
- Frantz R.Z., Sawicki S., Roos-Frantz F., Yevseyeva I. & Emmerich M.T.M. (2015), On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems. In: Hammoudi S., Maciaszek L., Teniente E. (red.) Proceedings of the 17th International Conference on Entreprise Information Systems. nr. 2: Scitepress. 260-267.
- Frantz R.Z., Sawicki S., Roos-Frantz F., Yevseyeva I. & Emmerich M. (2015), On Using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems. In: Hammoudi S., Maciaszek L., Teniente E. (red.) Proceedings of the 17th International Conference on Enterprise Information Systems. nr. 2 Barcelona: Scitepress. 260-267.
- Rijn S. van, Emmerich M.T.M., Reehuis E. & Bäck T.H.W. (2015), Optimizing Highly Constrained Truck Loadings Using a Self-Adaptive Genetic Algorithm. In: 2015 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 227-234.
- Emmerich M.T.M. & Nezhinsky A. (2015), Parameter Identification of Stochastic Gene Regulation Models by Indicator-based Evolutionary Level Set Approximation. In: Tantar A.A., Tantar E., Emmerich M.T.M., Legrand P., Alboaie L., Luchian H. (red.) EVOLVE 2015 - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation. nr. AISC 674 IASI: A.I.C. University Iasi. 39-40.
- Asep Maulana A., Jiang Z., Liu J., Bäck T.H.W. & Emmerich M.T.M. (2015), Reducing complexity in many objective optimization using community detection. In: 2015 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 3140-3147.
- Maulana A., Jiang Z., Liu J., Bäck T. & Emmerich M.T.M. (2015), Reducing Complexity in Many Objective Optimization Using Community Detection. In: 2015 IEEE Congress on Evolutionary Computation (CED).: IEEE. 3140-3147.
- Yevseyeva I., Basto-Fernandes V., Michael T. M.Emmerich & Moorsel A. van (2015), Selecting Optimal Subset of Security Controls, Procedia Computer Science 64: 1035-1042.
- Zhang X., Wu J., Duan C., Emmerich M.T.M. & Bäck T.H.W. (2015), Towards robustness optimization of complex networks based on redundancy backup. In: 2015 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 2820-2826.
- Leuven J., Emmerich M., Reehuis E. & Bäck T. (2015), User-derived mutation in highly constrained Truck Loading Optimization. In: Proceedings CEC 2015. Sendai, Japan: IEEE. 235-242.
- Leuven J., Emmerich M.T.M., Reehuis E. & Bäck T.H.W. (2015), User-derived mutation in highly constrained truck loading optimization. In: 2015 IEEE Congress on Evolutionary Computation (CEC).: IEEE. 235-242.
- Basto-Fernandes, V., Yevseyeva I., Frantz R.Z., Grilo C., Pérez Díaz N. & Michael T. M.Emmerich (2014), An Automatic Generation of Textual Pattern Rules for Digital Content Filters Proposal, Using Grammatical Evolution Genetic Programming, Procedia Technology 16: 806-812.
- Yevseyeva I., Guerreiro A.P., Michael T. M.Emmerich & Fonseca C.M. (2014), A Portfolio Optimization Approach to Selection in Multiobjective Evolutionary Algorithms. In: Parallel Problem Solving from Nature (PPSN XIII). nr. LNCS 8672: Springer. 672-681.
- Schütze O., Michael T. M.Emmerich, Xiong F.-R. & Sun J.-Q. (2014), Barrier Tree for Continuous Landscape by Means of Generalized Cell Mapping. In: EVOLVE - A Bridge between Probability, Set Oriented Optimization, and Evolutionary Computation (Short Paper Proceedings)..
- Wang P., Michael T. M.Emmerich, Li R., Tang K. & Bäck T.H.W. (2014), Convex Hull-Based Multi-objective Genetic Programming for Maximizing Receiver Operating Characteristic Performance, IEEE Transactions on Evolutionary Computation (99).
- Michael T. M.Emmerich & Nezshinsky A.E. (2014), Evolutionary Level Set Approximation Applied in Biological Systems Identification [extended abstract]. In: Preuss M. (red.) Proceedings PPSN 2014 - Workshop on Multimodal Optimization..
- Tantar A.-A., Tantar E., Sun J.-Q., Zhang W., Ding Q., Schütze O., Michael T. M.Emmerich, Legrand P., Del Moral P. & Coello Coello C.A. (red.) (2014), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V nr. Advances in Intelligent Systems and Computing 288: Springer International Publishing.
- Hupkens I., Michael T. M.Emmerich & Deutz A.H. (2014), Faster Computation of Expected Hypervolume Improvement nr. TR 2014-03. Leiden, The Netherlands: LIACS, Leiden University.
- Hernandez S., Adrian V., Schütze O. & Michael T. M.Emmerich (2014), Hypervolume Maximization via Set Based Netwon's Method. In: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V. nr. Advances in Intelligent Systems and Computing 288: Springer International Publishing. 15-28.
- Gheorge M., Snoeck M., Emmerich M.T.M., Bäck T.H.W., Goeman J. & Raz V. (2014), Major aging-associated RNA expressions change at two distinct age-positions, BMC Genomics 15: 132.
- Hao Wang, Michael T. M.Emmerich & Bäck T.H.W. (2014), Mirrored orthogonal sampling with pairwise selection in evolution strategies. In: Proceedings 29th Annual ACM Symposium on Applied Computing.: ACM. 154-156.
- Zhao J. Fernandes V.B., Licheng J., Yevseyeva I., Asep Maulana A., Li R., Bäck T.H.W. & ichael T. M.Emmerich (2014), Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm (. LIACS, Leiden University).
- Michael T. M.Emmerich, Deutz A.H. & Yevseyeva I. (2014), On Reference Point Free Weighted Hypervolume Indicators based on Desirability Functions and their Probabilistic Interpretation, Procedia Technology 16: 532-541.
- Yang K.,Michael T. M.Emmerich, Li R., Wang J. & Bäck T.H.W. (2014), Power Distribution Network Reconfiguration by Evolutionary Integer Programming. In: Proceedings Parallel Problem Solving from Nature (PPSN XIII). nr. LNCS 8672: Springer International Publishing. 11-23.
- Michael T. M.Emmerich & Deutz A.H. (2014), Time Complexity and Zeros of the Hypervolume Indicator Gradient Field. In: Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III. nr. Studies in Computational Intelligence 500: Springer International Publishling. 169-193.
- Keizer M.J., Bergen M.J. van & Michael T. M.Emmerich (2013), An interactive web-based database application for collaborative collection, storage and retrieval of data on volcanic lakes. In: Proceedings International Conference IAVCEI 2013 - Scientific Assembly of the International Association of Volcanology and Chemistry of the Earth's Interior..
- Veen B.D.V., Michael T. M.Emmerich, Yang Z., Bäck T.H.W. & Kok J.N. (2013), Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows. In: Vicente JMF, Sánchez JRÁ, Paz López F, Toledo-Moreo FJ (red.) Natural and Artificial Computation in Engineering and Medical Applications - 5th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2013, Mallorca, Spain, June 10-14, 2013. Proceedings, Part II. nr. 7931: Springer. 1-10.
- Basto-Fernandes V., Yevseyeva I. & Michael T. M.Emmerich (2013), A Survey of Diversity-Oriented Optimization. In: Michael T. M.Emmerich, Deutz A.H. (red.) EVOLVE 2013 - A Bridge Between Probability, Set Oriented Numerics, and Evolutionary Computation: Extended Abstract Proceedings.: Leiden University. 101-109.
- Shukla P.K., Michael T. M.Emmerich & Deutz A.H. (2013), A Theoretical Analysis of Curvature Based Preference Models. In: Proceedings Seventh International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013). nr. Lecture Notes in Computer Science: Springer-Verlag. 367-382.
- Zefferer M., Bartz-Beielsteen T., Naujoks B. & Wagner T. Emmerich M.T.M. (2013), Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets. In: Proceedings Evolutionary Multi-Criterion Optimization, EMO 2013. nr. LNCS 7811: Springer-Verlag. 756-770.
- Michael T. M.Emmerich, Deutz A.H., Kruisselbrink J.W. & Shukla P.K. (2013), Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation. In: Proceedings Seventh International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013). nr. Lecture Notes in Computer Science: Springer-Verlag. 111-127.
- Wang P.,Michael T. M.Emmerich, Li R., Tang K., Xin Y. & Bäck T.H.W. (2013), Convex Hull-Based Multi-objective for Genetic Programming for Maximizing ROC Performance.
- Michael T. M.Emmerich & Deutz A.H. (red.) (2013), EVOLVE 2013 - A Bridge Between Probability. Set Oriented Numerics, and Evolutionary Computation - Short Paper and Extended Abstract Proceedings: LIACS, Leiden University.
- Michael T. M.Emmerich, Deutz H.A., Schütze O., Bäck T.H.W., Tantar E., Tantar A.-A., Del Moral P., Legrand P., Bouvry P. & Coello C.C. (red.) (2013), EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV Advances in Intelligent Systems and Computing: Springer-Verlag.
- Stein B. van, Michael T. M.Emmerich & Yang Z. (2013), Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded Barrier Trees. In: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV.: Springer International Publishing. 75-89.
- Hupkens I. & Michael T. M.Emmerich (2013), Logarithmic-Time Updates in SMS-EMOA and Hypervolume-Based Archiving. In: EVOLVE - A bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV.: Springer International Publishing. 155-169.
- Li R., Michael T. M.Emmerich, Eggermont J., Bäck T.H.W., Schützand M., Dijkstra J. & Reiber J.H.C. (2013), Mixed Integer Evolution Strategies for Parameter Optimization, Evolutionary Computation Journal 21(1): 29-64.
- Reehuis E.J.J., Olhofer M., Michael T. M.Emmerich, Sendhoff B. & Bäck T.H.W. (2013), Novelty and Interestingness Measures for Design-space Exploration. In: Proceedings 15th Annual Conference on Genetic and Evolutionary Computation - GECCO'13.: ACM Press. 1541-1548.
- Michael T. M.Emmerich, Deutz A.H. & Kruisselbrink J.W. (2013), On Quality Indicators for Black-Box Level Set Approximation. In: Proceedings EVOLVE - A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation.. 157-185.
- Guerreiro A.P., Fonseca C.M. & Michael T. M.Emmerich (2012), A Fast Dimension-Sweep Algorithm for the Hypervolume Indicator in Four Dimensions. In: Proceedings 24th Canadian Conference on Computational Geometry, CCCG 2012.. 77-82.
- Wink S., Bäck T.H.W. & Michael T. M.Emmerich (2012), A Meta-Genetic Algorithm for Solving the Capacitated Vehicle Routing Problem. In: IEEE Congress on Evolutionary Computation 2012.. 1-8.
- Michael T. M.Emmerich, Deutz A.H., Kruisselbrink J.W. & Reehuis E. (2012), Evolutionary Approximation of Level Sets. In: EVOLVE 2012, A bridge between probability, set-oriented numerics, and evolutionary computation..
- Zaeferer M., Bartz-Beielstein T., Naujoks B., Wagner T & Michael T. M.Emmerich (2012), Model-assisted Multi-criteria Tuning of an Event Detection Software under Limited Budgets, Schriftenreihe CIplus 10.
- Horst Eelke van der, Marques-Gallego P., Mulder-Krieger Thea, Veldhoven J.P.D. van, Kruisselbrink J.W., Aleman A., Michael T. M.Emmerich, Brussee J., Bender Andreas & IJzerman A.P. (2012), Multi-Objective Evolutionary Design of Adenosine Receptor Ligands, Journal of Chemical Information and Modeling 52(7): 1713-1721.
- Etemaadi R.,Michael T. M.Emmerich & Chaudron M.R.V. (2012), Problem-specific Search Operators for Metaheuristic Software Architecture Design. In: Proceedings of Search Based Software Engineering - 4th International Symposium, SSBSE 2012.: Springer. 267-272.
- Custodio A.L.,Michael T. M.Emmerich & Madeira J.F.A. (2012), Recent Developments in Derivative-Free Multiobjective Optimisation, Computational Technology Reviews 5: 1-30.
- Fonseca C.M., Yevseyeva I. & Michael T. M.Emmerich (2012), Risk and return in evolutionary multiobjective optimization. In: Dagstuhl Seminar on Learning in Multiobjective Optimization..
- Hopfe C., Michael T. M.Emmerich, Marijt R. & Hensen J. (2012), Robust multi-criteria design optimization in building design. In: BSO12, Proceedings of the 1st IBPSA-England Conference Building Simulation and Optimization.: International Building Performance Simulation Association. 118-125.
- Michael T. M.Emmerich, Deutz A.H. & Kruisselbrink J.W. (2012), The Cone-Based Hypervolume Indicator: Definition, Computation and Interpretation: LIACS, Universiteit Leiden.
- Sanchez-Faddeev H., Michael T. M.Emmerich, Verbeek F.J., Henry A.H., Grimshaw S., Spaink H.P., Vlijmen H.W.T. van & Bender A. (2012), Using Multiobjective Optimization and Energy Minimization to Design an Isoform-Selective Ligand of the 14-3-3 Protein. In: Margaria T., Steffen B. (red.) Leveraging Applications of Formal Methods, Verification and Validation. Applications and Case Studies (ISoLA 2012).: Springer. 12-24.
- Bürklen S., Deb K., Michael T. M.Emmerich, Kuefer K., Naujoks B., Ng A.H.C., Oyama A., Poles S., Ulrich T. & Witting K. (2012), What and how can we learn from Pareto fronts and sets? Working Group Pareto Sense. In: Proceedings Dagstuhl Seminar on Learning in Multiobjective Optimization.. 81-81.
- Li Rui, Michael T. M.Emmerich, Eggermont J., Bäck T.H.W., Schütz M., Dijkstra J. & Reiber J.H.C. (2012), Mixed Integer Evolution Strategies for Parameter Optimization, Evolutionary Computation Journal : 1-38.
- Kruisselbrink J.W., Michael T. M.Emmerich & Bäck T.H.W. (2011), An Archive Maintenance Scheme for Finding Robust Solutions. In: Parallel Problem Solving from Nature (PPSN XI).: Springer. 214-223.
- Li Rui, Etemaadi R., Michael T. M.Emmerich & Chaudron M.R.V. (2011), An evolutionary multiobjective optimization approach to component-based software architecture design. In: Proceedings IEEE Congress on Evolutionary Computation (CEC 2011).: IEEE. 432-439.
- Li Rui, Etemaadi R., Michael T. M.Emmerich & Chaudron M.R.V. (2011), Automated Design of Software Architectures for Embedded Systems using Evolutionary Multiobjective Optimization. In: Proceedings Workshop on Applied Combinatorial Optimization..
- Michael T. M.Emmerich & Fonseca C.M. (2011), Computing hypervolume contributions in low dimensions: asymptotically optimal algorithm and complexity results. In: EMO'11: Proceedings of the 6th international conference on Evolutionary multi-criterion optimization.: Springer. 121-135.
- Kruisselbrink J.W., Michael T. M.Emmerich, Deutz A.H. & Bäck T.H.W. (2011), Exploiting Overlap When Searching for Robust Optima. In: Parallel Problem Solving from Nature (PPSN XI).: Springer. 63-72.
- Michael T. M.Emmerich, Deutz A.H. & Klinkenberg J.W. (2011), Hypervolume-based expected improvement: Monotonicity properties and exact computation. In: Proceedings of IEEE Congress on Evolutionary Computation (CEC 2011).: IEEE. 2147-2154.
- Li Rui, Michael T. M.Emmerich, Eggermont J., Bäck T.H.W., Dijkstra J., Reiber H. & Schuetz M. (2011), Mixed Integer Evolution Strategies for Parameter Optimization, Evolutionary Computation Journal .
- Reehuis E., Kruisselbrink J.W., Deutz A.H., Bäck T.H.W. & Michael T. M.Emmerich (2011), Multiobjective optimization of water distribution networks using SMS-EMOA. In: Proceedings Evolutionary and Deterministic Methods for Design, Optimization and Control.: CIMNE. 269-279.
- Wagner T, Michael T. M.Emmerich, Deutz A.H. & Ponweiser W. (2011), On Expected-Improvement Criteria for Model-based Multi-objective Optimization. In: Parallel Problem Solving from Nature (PPSN XI).: Springer. 718-727.
- Michael T. M.Emmerich, Deutz A.H. & Kruisselbrink J.W. (2011), On Quality Indicators for Finite Level-Set Representations. In: EVOLVE 2011 A bridge between Probability, Set Oriented Numerics and Evolutionary Computation..
- Sella L., Michael T. M.Emmerich & Hille S.C. (2011), Simulations of Signaling Networks in B. Subtilis. In: Proceedings 8th European Conference on Mathematical and Theoretical Biology and Annual Meeting of the Society for Mathematical Biology..
- Kruisselbrink J.W., Reehuis E., Deutz A.H., Bäck T.H.W. & Michael T. M.Emmerich (2011), Using the uncertainty handling CMA-ES for finding robust optima. In: Proceedings of the 13th annual conference on Genetic and evolutionary computation.: ACM. 877-884.
- Shir O.M., Michael T. M.Emmerich & Bäck T.H.W. (2010), Adaptive niche radii and niche shapes approaches for niching with the cma-es, Evolutionary Computation Journal 18(1): 97-126.
- Kruisselbrink J.W., Michael T. M.Emmerich & Bäck T.H.W. (2010), An Archive Based Method for Applying Evolutionary Algorithms to Find Robust Optima: Universiteit Leiden.
- Kruisselbrink J.W., Michael T. M.Emmerich & Bäck T.H.W. (2010), An Archive Maintenace Scheme for Finding Robust Solutions. In: Parallel Problem Solving from Nature (PPSN XI).: Springer. 214-223.
- Horst E. van der, Peironcely Julio E., IJzerman A.P., Beukers M.W., Lane J.R., Vlijmen H. van, M.T.M. Emmerich, Okuno Yasushi & Bender A. (2010), A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization, BMC bioinformatics 11: 316.
- Klinkenberg J.W., Michael T. M.Emmerich, Deutz A.H., Shir O.M. & Bäck T.H.W. (2010), A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization. In: Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems.: Springer-Verlag.
- Kuijl A. v.d., Michael T. M.Emmerich & Li Rui (2010), A robust multi-objective resource allocation scheme incorporating uncertainty and service differentiation, Concurrency and Computation: Practice and Experience 22(3): 314-328.
- Kruisselbrink J.W., Michael T. M.Emmerich, Deutz A.H. & Bäck T.H.W. (2010), A Robust Optimization Approach using Kriging Metamodels for Robustness Approximation in the CMA-ES. In: IEEE Congress on Evolutionary Computation (CEC 2010).: IEEE. 1-8.
- Doddareddy M.R., Westen G.J.P. van, Horst Eelke van der, Peironcely Julio E., Corthals Frans, IJzerman A.P., Michael T. M.Emmerich, Jenkins Jeremy L. & Bender Andreas (2010), Chemogenomics: Looking at biology through the lens of chemistry, Statistical Analysis and Data Mining 2(3): 149-160.
- Horst Eelke van der, Kruisselbrink J.W., Aleman A., Emmerich M.T.M., Bender Andreas & IJzerman A.P. (2010), Evolutionary Design of Selective Adenosine Receptor Ligands [poster], 2: 1-1.
- Michael T. M.Emmerich, Deutz A.H., Li R. & Kruisselbrink J.W. (2010), Getting lost or getting trapped: on the effect of moves to incomparable points in multiobjective hillclimbing. In: GECCO (Companion).. 1963-1966.
- Michael T. M.Emmerich, Bäck T.H.W. & Li R. (2010), Improving Medical Image Analysis by Optimization, Eureka magazine : 8-11.
- Michael T. M.Emmerich & Deutz A.H. (2010), Variance Monotonicity of the Expected Improvement of the 2D Hypervolume in Pareto Optimization. Leiden: Universiteit Leiden.
- Doddareddy M.R., Westen G.J.P. van, Horst E. van der, Peironcely Miguel J.E., Corthals F., IJzerman A.P., Emmerich M.T.M., Jenkins J.L. & Bender A. (2009), Chemogenomics: Looking at biology through the lens of chemistry, Statistical Analysis and Data Mining 2: 149-160.
- Michael T. M.Emmerich, Li B.V.Y., Bender Andreas, Faddiev E., Kruisselbrink J.W., Deutz A.H., Horst Eelke van der, IJzerman Adriaan P. & Bäck T.H.W. (2009), Analyzing Molecular Landscapes using Random walks and Information Theory [poster], Chemistry Central Journal 3(Suppl. 1).
- Doddareddy M.R., Westen G.J.P. van, Horst E. van der, Peironcely J., Corthals F., IJzerman A.P., Emmerich M.T.M., Jenkins J.L. & Bender A. (2009), Chemogenomics: Looking at biology through the lens of chemistry, Statistical Analysis and Data Mining 2(3): 149-160.
- Kruisselbrink J.W., Michael T. M.Emmerich, Bäck T.H.W., Bender A., IJzerman A.P. & Horst E. van der (2009), Combining aggegration with pareto optimization: A case study in evolutionary molecular design. In: Evolutionary Multi-Criterion Optimization, 5th International Conference, EMO 2009.: Springer. 453-467.
- Shir O.M., Preuss M., Naujoks B. & Michael T. M.Emmerich (2009), Enhancing decision space diversity in evolutionary multiobjective algorithms. In: Evolutionary Multi-Criterion Optimization, 5th International Conference, EMO 2009.: Springer. 95-109.
- Kruisselbrink J.W., Aleman A., Michael T. M.Emmerich, IJzerman A.P., Bender A., Bäck T.H.W. & Horst E. van der (2009), Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching. In: Proceedings of the 11th Annual conference on Genetic and Evolutionary Computation (GECCO). New York: ACM. 217-224.
- Chen J, Michael T. M.Emmerich, Li R., Kok J.N. & Bäck T.H.W. (2009), How to Do Recombination in Evolution Strategies: An Empirical Study. In: Third International Work conference on the Interplay between Natural and Artificial Computation.. 223-232.
- Kruisselbrink J.W., Michael T. M.Emmerich & Bäck T.H.W. (2009), On the limitations of adaptive resampling in using the student's t-test evolution strategies. In: Proceedings of the 11th Annual conference on Genetic and Evolutionary Computation (GECCO). New York: ACM. 2649-2656.
- Li R., Michael T. M.Emmerich, Eggermont J., Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J & Reiber H. (2009), Optimizing a medical image analysis system using mixed-integer evolution strategies. In: S. Cagnoni et al (red.) Evolutionary Image Analysis and Signal Processing.: Springer.
- Li R., Michael T. M.Emmerich, Eggermont J., Dijkstra J & Reiber J.H.C. (2009), Radial Basis Function Network Models for metamodeling and Optimization in Mixed-Integer Spaces. Enschede: the University of twente. [overig]
- Michael T. M.Emmerich, Li B.V.Y., Bender A., Faddiev E., Kruisselbrink J.W., Deutz A.H., Horst E. van der, IJzerman A.P. & Bäck T.H.W. (2008), Analysing Molecular Landscapes Using Random Walks and Information Theory. In: German Conference on Chemoinformatics. Goslar. 73.
- Michael T. M.Emmerich, Hopfe C., Marijt R., Hensen J. & Struck C. (2008), Evaluating Optimization Methodologies for Future Integration in Building Performance Tools. In: Ian Parmee (red.) ACDM 2008..
- Kuijl A. v.d., Michael T. M.Emmerich & Li Rui (2008), A novel multi-objective optimization scheme for grid resource allocation. In: MGC 2008.. 7.
- Kuijl A. v.d., Li Rui & Michael T. M.Emmerich (2008), A novel multi-objective optimization scheme for grid ressource allocation. In: 6th International Workshop on Middleware for Grid Computing - MGC 2008..
- Klinkenberg W., Michael T. M.Emmerich, Deutz A.H., Shir O.M. & Bäck T.H.W. (2008), A Reduced-Cost SMS-EMOA using Kriging, Self-Adaptation, and Parallelization. In: M. Ehrgott et al (red.) Conference on Multicriteria Decision Making 2008..
- Michael T. M.Emmerich, Kruisselbrink J.W., Horst E. van der, IJzerman A.P., Bender A. & Bäck T.H.W. (2008), Combined Interactive and Automated Adaptive Search for Molecular Design. In: Proceedings of Adaptive Computing in Design and Manufacture 2008.: IPCC.
- Klinkenberg J.W., Michael T. M.Emmerich & Deutz A.H. (2008), Expected improvement of the S-metric for finite Pareto front approximations. In: Conference on Multicriteria Decision Making 2008.: M. Ehrgott et al.
- Li R., Michael T. M.Emmerich, Eggermont J., Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2008), Metamodel-Assisted Mixed Integer Evolution Strategies and their Application to Intravascular Ultrasound Image Analysis. In: Proceedings of IEEE CEC. Hong Kong. 2764-2771.
- Michael T. M.Emmerich, Li R., Zhang A., Flesch I. & Lucas P. (2008), Mixed-Integer Bayesian Optimization Utilizing A-Priori Knowledge on Parameter Dependences. In: 20th Belgian-Netherlands Conference on Artificial Intelligence (BNAIC). Enschede.
- Li R., Eggermont J., Shir O.M., Michael T. M.Emmerich, Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2008), Mixed-Integer Evolution Strategies with Dynamic Niching. In: Günter Rudolph, Thomas Jansen, Simon M. Lucas, Carlo Poloni, Nicola Beume (red.) PPSN.: Springer. 246-255.
- Eggermont J., Li R., Bovenkamp E.G.P., Marquering H.A., Michael T. M.Emmerich, Lugt A. van der, Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2008), Optimizing Computed Tomographic Angiography Image Segmentation Using Fitness Based Partitioning. In: Applications of Evolutionary Computing. Heidelberg: Springer Berlin / Heidelberg. 275-284.
- Michael T. M.Emmerich, Deutz A.H. & Klinkenberg J.W. (2008), The computation of the expected improvement in dominated hypervolume of Pareto front approximations. Leiden: Universiteit Leiden.
- Urselmann M., Michael T. M.Emmerich, Till J., Sand G. & Engell S. (2007), Design of problem-specific evolutionary algorithm/mixed-integer programming hybrids: two-stage stochastic integer programming applied to chemical batch scheduling, Engineering Optimization 39(5): 529-549.
- Michael T. M.Emmerich, Deutz A.H. & Beume N. (2007), Gradient-Based/Evolutionary Relay Hybrid for Computing Pareto Front Approximations Maximizing the S-Metric, Hybrid Metaheuristics : 140-156.
- Shir O.M., Michael T. M.Emmerich & Bäck T.H.W. (2007), Self-Adaptive Niching CMA-ES with Mahalanobis Metric. In: proceedings of IEEE Congress on Evolutionary Computation.: Research Publishing Services.
- Michael T. M.Emmerich & Deutz A.H. (2007), Test Problems based on Lame Superspheres. In: Evolutionary Multiobjective Optimization 2007 (EMO2007).: Springer. 922-936.
- Shir O.M., Michael T. M.Emmerich, Bäck T.H.W. & Vrakking M.J.J. (2007), The Application of Evolutionary Multi-Criteria Optimization to Dynamic Molecular Alignment. In: proceedings of IEEE Congress on Evolutionary Computation.: Research Publishing Services.
- Li R., Eggermont J., Michael T. M.Emmerich, Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2007), Towards Dynamic Fitness Based Partitioning for IntraVascular UltraSound Image Analysis. In: EvoWorkshops 2007.. 391-398.
- Eggermont J., Bovenkamp E.G.P., Li R., Michael T. M.Emmerich, Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2006), Extending nk landscapes to the mixed-integer domain. In: 18th Belgium-Netherlands Conference on Artificial Intelligence..
- Michael T. M.Emmerich, Li R., Eggermont J., Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2006), Optimizing Parameters of Coronary Vessel Image Analysis using Evolution Strategies. In: 18th Belgium-Netherlands Conference on Artificial Intelligence..
- Michael T. M.Emmerich & Deutz A.H. (2006), A family of test problems with pareto-fronts of variable curvature based on super-spheres. In: MCDM 2006..
- Michael T. M.Emmerich, Shir O.M. & Bäck T.H.W. (2006), Multi-criteria optimization in laser pulse shaping using evolutionary algorithms and kriging metamodels. In: MCDM 2006..
- Jakumeit J., Michael T. M.Emmerich & Hediger F. (2006), Inverse modeling and numerical optimization of heater temperatures in a bridgman process. In: Modeling of Casting, Welding and Advanced Solidification Processes XI..
- Li Rui, Michael T. M.Emmerich, Bovenkamp E.G.P., Eggermont J., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2006), Mixed-Integer Evolution Strategies and Their Application to Intravascular Ultrasound Image Analysis. In: F. Rothlauf et al (red.) 8th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing (EvoIASP).: Springer Verlag. 415-426.
- Michael T. M.Emmerich, Hundemer J., Varcol M.C., Naujoks B. & Abdel-Maksoud M. (2006), Design optimization of ship propellers by means of advanced metamodel-assisted evolution strategies. In: International Conference on Design Optimization..
- Michael T. M.Emmerich, Urselmann M., Till J., Sand G. & Engell S. (2006), Hybrid ea/mip method for solving two-stage stochastic programming problems in chemical batch scheduling. In: 7th International Conference on Adaptive Computing in Design and Manufacture..
- Li Rui, Michael T. M.Emmerich, Eggermont J., Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2006), Mixed-Integer NK Landscapes. Parallel Problem Solving from Nature. In: PPSN.. 42-51.
- Li R., Michael T. M.Emmerich, Eggermont J., Bovenkamp E.G.P., Bäck T.H.W., Dijkstra J. & Reiber J.H.C. (2006), Mixed-Integer Optimization of Coronary Vessel Image Analysis using Evolution Strategies. In: In M. Keijzer et al (red.) 8th annual conference on Genetic and evolutionary computation.. 1645-1652.
- Breukelaar R., Michael T. M.Emmerich & Bäck T.H.W. (2006), On interactive evolution strategies. In: Applications of Evolutionary Computing. Berlin / Heidelberg: Springer. 530-541.
- Li R., Michael T. M.Emmerich, Bäck T.H.W., Bovenkamp E.G.P., Eggermont J., Dijkstra J. & Reiber J.H.C. (2006), Optimizing Parameters of Intravascular Ultrasound Image Analysis Systems using Mixed-Integer Evolution Strategies. In: Adaptive Computing in Design and Manufacture (ACDM).: IP-CC Press. 283-284.
- Michael T. M.Emmerich (2006), Sms-emoa: Multiobjective selection based on dominated hypervolume, European Journal of Operational Research .
- Till J., Sand G., Engell S., Michael T. M.Emmerich & Schönemann L. (2005), A hybrid algorithm for solving two-stage stochasticinteger problems by combining evolutionary algorithms and mathematical programming methods. In: Puigjaner L. (red.) Proceedings European Symposium Computer Aided Process Engineering (ESCAPE-15). Computer-aided Chemical Engineering Amsterdam: Elsevier. 187-192.
- Michael T. M.Emmerich, Beume N. & Naujoks B. (2005), An EMO algorithm using the hypervolume measure as selection criterion. In: Coello Coello C.A., Hernández Aguirre A., Zitzler E. (red.) Proceedings Evolutionary Multi-Criterion Optimization: Third Int'l Conference (EMO 2005). Berlin: Springer-verlag. 62-76.
- Preuss M., Schönemann L. & Michael T. M.Emmerich (2005), Counteracting Genetic Drift and Disruptive Recombination in (mu + lambda)-EA on Multimodal Fitness Landscapes. In: Beyer H.-G., O'Reilly U.-M. (red.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2005).: ACM. 865-872.
- Jakumeit J. & Michael T. M.Emmerich (2005), Inverse modelling and numerical optimization of heater temperatures in a Bridgman process. In: Proceedings of MCWASP Conference Modeling of Casting, Welding and Advanced Solidification Processes XI 2005. 2005.
- Naujoks B., Beume N. & Michael T. M.Emmerich (2005), Metamodel-assisted SMS-EMOA applied to airfoil optimization tasks. In: Proceedings Evolutionary and Deterministic Methods for Design Optimisation and Control with Applications to Industrial and Societal Problems (EUROGEN'05)..
- Naujoks B., Beume N. & Michael T. M.Emmerich (2005), Multi-objective optimisation using S-metric selection: Application to three-dimensional solution spaces. In: McKay B., et al. (red.) Proceedings 2005 Congress on Evolutionary Computation (CEC'05). Piscataway NJ: IEEE Press. 1282-1289.
- Bäck T.H.W. & Michael T. M.Emmerich (2002), Evolution Strategies for Optimisation in Engineering Applications. In: Mang, H.A., Rammerstorfer, F.G., Eberhardsteiner, J. (red.) Proceedings Fifth World Congress on Computational Mechanics..
- Michael T. M.Emmerich, Giotis A., Özdemir M., Bäck T.H.W. & Giannakoglu K. (2002), Metamodel-Assisted Evolution Strategies. In: Merelo Guervos, J.J., Adamidis, P., Beyer, H.G., Fernandez-Villacanas, J.L., Schwefel, H.P. (red.) Proc. of the Seventh International Conference on Parallel Problem Solving from Nature. Berlin: Springer. 361-370.
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